Recent developments in networking technology have allowed delivery of digital data through wired/wireless networks with bandwidths that are large enough to accommodate delivery of rich multimedia data to end terminals. The mobile device manufacturers in turn, have developed terminals that can gracefully handle the multimedia content. However, a unified multimedia processing architecture for the mobile terminals does not exist and the mobile market accommodates diverse terminals having significantly different resource handling capabilities. This diversity necessitates the tailoring of the content according to the capabilities of the individual terminals. While it is possible to author content for a specific class of devices such as the PDA's or mobile phones, adapting the content individually for each user terminal results in higher user satisfaction. Such a dynamic adaptation scheme also accounts for the possible changes of state of a user terminal. The state of a user terminal can vary frequently, for instance as the end-user changes his physical location, the networks and the transmission channels that the mobile terminal accesses also change. Then the environmental conditions and the user preferences need to be re-evaluated to provide the user with a better multimedia experience.
Various methodologies have been proposed that deal with the problem stated above. A fundamental step towards the solution of the problem is to determine, in a methodical way, the attributes of the multimedia data that make it an ideal candidate to provide maximum user satisfaction. There exist three main approaches for evaluating the quality of digital images and video in the literature;                1. Methods utilizing objective metrics (MSE, PSNR)        2. Methods evaluating the satisfaction a user will get from viewing multimedia data using models of the Human Visual System (HVS)        3. Methods using utility values elicited from human subjects via subjective evaluation tests        
It should be emphasized that the methods mentioned above focus on the differences in the content, and the capabilities of the terminals at which the content is consumed is not considered. It is well known that objective metrics, such as PSNR or MSE, are highly uncorrelated with the human perception of quality. Furthermore, due to the extreme complexity of the HVS, a complete and precise HVS model that has been widely accepted does not yet exist. As a result, utilizing subjective tests to evaluate video quality is still accepted to be the most accurate way of modeling human responses. Nevertheless, this approach is tedious and expensive. The dependency of the results on the testing environment, as well as the experience and motivation of the human subjects is another issue that needs to be considered when using this methodology.
Methods that Utilize Utility Functions or Similar Constructs to Model User Viewing Satisfaction Also Exist:
Among the known techniques is a system to adapt multimedia web content to match the capabilities of a requesting device introduced in R. Mohan, J. R. Smith, and C.-S. Li, “Adapting Multimedia Internet Content for Universal Access,” IEEE TRANSACTIONS ON MULTIMEDIA, VOL. 1, NO. 1, MARCH 1999. The system involves an InfoPyramid, which creates and stores multi-modal and multi-resolution representations of the multimedia content. Using this representation, a “customizer” selects the representation of the content from various available versions. Considering the diversity of the terminals that can be used to access multimedia content, an optimal representation for each different terminal cannot be obtained from a predetermined set of representations by using such a method.
The first reference to utility theory in the context of video adaptation appears in P. Bocheck, Y. Nakajima and S.-F. Chang, “Real-time Estimation of Subjective Utility Functions for MPEG-4 Video Objects,” Proceedings of IEEE Packet Video Workshop (PV'99), New York, USA, April, 1999. The method, albeit mentioning the possible incorporation of the utility theory into the context of video adaptation, refrains from stating the details of how the method can be facilitated.
In a more theoretical approach, only a conceptual framework that models adaptation, as well as resource, utility and the relationships in between, are presented in S. F. Chang, “Optimal Video Adaptation and Skimming Using a Utility-Based Framework,” Tyrrhenian International Workshop on Digital Communications (IWDC-2002) Capri Island, Italy September 2002. While objective measures, such as PSNR, coherence, temporal smoothness are used to measure utility, the optimal video adaptation problem is formulated as finding the adaptation operation that maximizes the utility of the adapted entity, given the original entity and resource constraints. However, the objective measures fail to model human satisfaction adequately. Hence, for obtaining an acceptably accurate model, a multitude of attributes need to be extracted from the video, and such a procedure significantly increases the computational complexity of the system.
A content-based utility function predictor is also proposed in Y. Wang, J.-G. Kim, S.-F. Chang, “Content-Based Utility Function Prediction For Real-Time MPEG-4 Video Transcoding,” IEEE ICIP 2003, In this method, the system extracts compressed domain features in real time and uses content-based pattern classification and regression to obtain a prediction to the utility function. Nevertheless, the utility value, corresponding to a given adaptation of a video, is presented as a function of the video bit-rate, which contradicts the subjective nature of the utility concept.
Utility Theory strives to obtain the satisfaction that any given resource provides to the owner of the resource, as a function of the amount of that resource owned. Generally the relationship between the satisfaction and the amount of resource is highly subjective, i.e. might be different for each individual. The main function of Utility Theory in these types of problems is fitting an objective model to this subjective relation. When this is accomplished, the change in the user satisfaction as a result of a change in the amount of the resource can be calculated. Utility Theory is commonly employed in the fields of statistics, economics, and management. Particularly in games of fortune like the lotteries, various marketing and corporate strategy applications the theory has enjoyed wide spread popularity.
Some of the Methodologies that Employ Utility Theory in Practical Applications are Presented Below:
Patent application EP 1143380, pertains to predicting the decision of a consumer trying to make a selection among various alternatives, by using the decisions that the user or other users with similar behavior patterns have made in the past. The patent does not include the application of the proposed approach to a specific problem, and the method is discussed as a general decision making mechanism. Although the proposed approach is practical for simple formulations, it is not applicable to problems like modeling the satisfaction a user gets form watching a video clip where many variables having complex relationships with each other are involved.
Patent application GB2399195 pertains to a system that automatically assesses the performances of web sites. The users are separated into classes depending on their web site habits i.e. the total time they spend logged on to the site, the number of items they buy etc. An intelligent agent automatically imitates the behavior of a particular class of customers and interacts with the web site accordingly. The response of the web site to the interactions are recorded and input to a utility function. The value of the function is then used as a figure of merit for that site for the client class that is being tested. The proposed method is specialized for a particular application and is not suitable for determining the satisfaction a user gets from watching a video clip.
Patent application U.S. Pat. No. 6,484,152 relates to a system that chooses the best portfolio from a pool of stocks so as to meet the needs of each individual customer to the fullest extent possible. After collecting the necessary information such as the amount of money that will be invested, the risk that the customer is willing to take etc. the system uses utility functions to determine the optimum portfolio that will suit the needs of the customer. The method needs to elicit substantial amount of information from each individual user each time the system is used so it is not applicable to determining the utility of video clips.
In patent application U.S. Pat. No. 20,030,033,190, a system that determines if an on-line shopper is converted into a purchaser of an item as a result of promotions offered by an online vendor is proposed. A model partially based on regression and partially on utility theory is constructed using the customer profile, the log information, products currently on sale and the offered promotions. When the data corresponding to a new shopper is fed to the system, the percentage likelihood that s/he will be converted into a purchaser is calculated. The methodology is specifically designed for the online shopper problem and is not suitable for use in the utility formulation of satisfaction on watching video clips.